Street-fashion photographs contain a large amount of noise, which hinders the precise detection of combinations of clothes that people wear. To remove the noise, we performed image pre-processing as the final step in the following manner. We identified human bodies in the photographs using OpenPose [1]}, an ML algorithm for object recognition, and removed as much of the background image as possible. Subsequently, we trimmed the subject's head to focus on clothing items based on the head position, which was detected using OpenPose. Fig. REF  shows an overview of the data contained in CAT STREET. The total number of images in the database is 14,679.
